{"url":"/dataset/homebreweddb","name":"HomebrewedDB","full_name":null,"description_markdown":"**HomebrewedDB** is a dataset for 6D pose estimation mainly targeting training from 3D models (both textured and textureless), scalability, occlusions, and changes in light conditions and object appearance. The dataset features 33 objects (17 toy, 8 household and 8 industry-relevant objects) over 13 scenes of various difficulty. It also consists of a set of benchmarks to test various desired detector properties, particularly focusing on scalability with respect to the number of objects and resistance to changing light conditions, occlusions and clutter.","description_withheld":null,"homepage":"http://campar.in.tum.de/personal/ilic/homebreweddb/index.html","introduced_date":"2019-04-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/homebreweddb-rgb-d-dataset-for-6d-pose","title":"HomebrewedDB: RGB-D Dataset for 6D Pose Estimation of 3D Objects","first_author":"Roman Kaskman","url":null},"license":{"name":"CC0 1.0 Universal","url":"http://campar.in.tum.de/personal/ilic/homebreweddb/files/LICENSE.html"},"modalities":[{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"6D Pose Estimation","url":"/task/6d-pose-estimation-1","datasets_with_task":"/datasets/task/6d-pose-estimation-1"}],"languages":[],"variants":["HomebrewedDB"],"data_loaders":[],"num_papers_in_archive":26,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}